Publisher: K-i-s-publishing
Disaster Recovery and Business Continuity. A quick guide for organisations and business managers
IT Governance Publishing, Thejendra B.S
This book delves into disaster recovery (DR) and business continuity (BC), offering practical strategies for organizations to prepare for and manage disruptions. It starts by defining core concepts of DR and BC, highlighting their role in crisis management. Early chapters explore business impact analysis, data protection, and risk assessment, while examining common IT and non-IT disasters like data loss, cyberattacks, and communication failures.Later sections focus on specific disaster scenarios, such as virus attacks, software failures, and data center risks, offering prevention methods and recovery plans. It also addresses human factors in DR, covering IT staff and contractor management, and the risks tied to outsourcing and project failures.In addition to IT risks, the book explores non-IT disasters, including health crises, financial challenges, and natural events, with strategies for mitigation. The final chapters provide guidance on creating and testing contingency plans, featuring checklists and mock run procedures. This book empowers readers to design, implement, and maintain effective DR and BC plans for their organization’s needs.
Abhilash G B
VMware vCenter Site Recovery manage is an orchestration tool used to automate disaster recovery in a manner that no other solution does. It is programmed to leverage array-based replication and VMware's proprietary vSphere Replication engine.The book begins by talking about the architecture of SRM and guides you through the procedures involved in installing and configuring SRM to leverage array-based replication. You will then learn how to protect your virtual machines by creating Protection Groups and validate their recoverability by testing recovery plans and even performing failover and failback. Moving on, you will learn how to install and configure vSphere Replication as a standalone disaster recovery solution. It also guides you through the procedures involved in configuring SRM to leverage vSphere replication.Finally, you will learn how to deploy and configure vRealize Orchestrator and its plugin for SRM and vSphere Replication.
Abhilash G B
This is a step-by-step guide that will help you understand disaster recovery using VMware vSphere Replication 5.5 and VMware vCenter Site Recovery Manager (SRM) 5.5. The topics and configuration procedures are accompanied with relevant screenshots, flowcharts, and logical diagrams that makes grasping the concepts easier. This book is a guide for anyone who is keen on using vSphere Replication or vCenter Site Recovery Manager as a disaster recovery solution. This is an excellent handbook for solution architects, administrators, on-field engineers, and support professionals. Although the book assumes that the reader has some basic knowledge of data center virtualization using VMware vSphere, it can still be a very good reference for anyone who is new to virtualization.
Nelson Enriquez, Samundar Singh Rathore
Business Intelligence is a type of technology that has been proven to support business decisions in an organization. MicroStrategy 9 is a fully-integrated BI platform that makes Business Intelligence faster, easier, and more user-friendly. It enables businesses to generate their own reports and dashboards without the need for technical knowledge.This practical, hands-on guide will provide Business Intelligence for executives, as well as enable BI reports and dashboards without the dependency of IT savvy personnel. It will allow you to design, build, and share business relevant data in hours, in a secure way, including mobile devices and show you how to leverage your transactional information.This example-oriented book looks at the value proposition of cloud computing and the MicroStrategy platform, and features practical exercises for BI reports and dashboard enablement, including the design phase and best practices for when we design a BI report.The book begins with an exploration of MicroStrategy along with typical business needs. Our focus then shifts to best practices for BI reports and dashboard definitions from the functional stand point, with easy-to-do exercises that will allow you to enable the reports in the platform. You will learn about scorecards and dashboards, along with sharing the reports. Next, you will get acquainted with cloud-based services provided by the MicroStrategy platform. By the end of this book, you will able to design, enable, and share BI reports and dashboards without the need for comprehensive technical knowledge, and leverage the latest technology on the market.
Fuheng Wu
As AI models grow to billions and trillions of parameters, distributed systems are essential for training and serving them. Many resources cover fragments of this domain, but none provide a full path from distributed training to inference and production deployment. This book fills that gap with practical, production-focused examples.It starts with GPU and memory estimation, data preparation, and an overview of GPU architecture, interconnects, and core parallelism strategies. You’ll learn training techniques including data parallelism for single and multi-node setups, parameter sharding for memory-efficient scaling, and methods to reduce memory usage in large models.The next section covers distributed inference and deployment. You’ll build high-performance systems using optimized attention, caching, operator fusion, and router-based designs. You’ll deploy on schedulers and container platforms with GPU-aware orchestration and assemble production stacks emphasizing reliability, scalability, and observability.The final section covers benchmarking, performance tuning, and trends like MoE models, edge - cloud co-ordination, and advanced parallelism. Each chapter includes tested code and debugging guidance.By the end, you’ll be able to build distributed AI systems that scale from a single GPU to large clusters.
Distributed Computing in Java 9. Leverage the latest features of Java 9 for distributed computing
Raja Malleswara Rao Malleswara Rao Pattamsetti
Distributed computing is the concept with which a bigger computation process is accomplished by splitting it into multiple smaller logical activities and performed by diverse systems, resulting in maximized performance in lower infrastructure investment. This book will teach you how to improve the performance of traditional applications through the usage of parallelism and optimized resource utilization in Java 9.After a brief introduction to the fundamentals of distributed and parallel computing, the book moves on to explain different ways of communicating with remote systems/objects in a distributed architecture. You will learn about asynchronous messaging with enterprise integration and related patterns, and how to handle large amount of data using HPC and implement distributed computing for databases. Moving on, it explains how to deploy distributed applications on different cloud platforms and self-contained application development. You will also learn about big data technologies and understand how they contribute to distributed computing. The book concludes with the detailed coverage of testing, debugging, troubleshooting, and security aspects of distributed applications so the programs you build are robust, efficient, and secure.
Distributed Computing with Go. Practical concurrency and parallelism for Go applications
V.N. Nikhil Anurag, Jinzhu Zhang, Pankaj Khairnar
Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula.
Francesco Pierfederici
CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications.This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more.